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    <div class="figcaption"><a href="https://distill.pub/2017/feature-visualization/#optimization">Visualizing individual neurons</a> make hidden layers somewhat meaningful, but misses interactions between neurons — it only shows us one-dimensional, orthogonal probes of the high-dimensional activation space.</div>
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    <div class="figcaption"><a href="https://distill.pub/2017/feature-visualization/#interaction">Pairwise interactions</a> reveal interaction effects, but they only show two-dimensional slices of a space that has hundreds of dimensions, and many of the combinations are not realistic.</div>
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    <div class="figcaption"><a href="https://distill.pub/2018/building-blocks/#what-does-the-network-see">Spatial activations</a> show us important combinations of many neurons by sampling the sub-manifold of likely activations, but they are limited to those that occur in the given example image.</div>
  </div>
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    <div class="figcaption">Activation atlases give us a bigger picture overview by sampling more of the manifold of likely activations.</div>
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